{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from mxnet import nd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['NDArray', '_Null', '__all__', '__builtins__', '__cached__', '__doc__', '__file__', '__loader__', '__name__', '__package__', '__spec__', '_internal', '_random_helper', 'current_context', 'exponential', 'exponential_like', 'gamma', 'gamma_like', 'generalized_negative_binomial', 'generalized_negative_binomial_like', 'multinomial', 'negative_binomial', 'negative_binomial_like', 'normal', 'normal_like', 'numeric_types', 'poisson', 'poisson_like', 'randint', 'randn', 'shuffle', 'uniform', 'uniform_like']\n"
     ]
    }
   ],
   "source": [
    "print(dir(nd.random))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function ones_like:\n",
      "\n",
      "ones_like(data=None, out=None, name=None, **kwargs)\n",
      "    Return an array of ones with the same shape and type\n",
      "    as the input array.\n",
      "    \n",
      "    Examples::\n",
      "    \n",
      "      x = [[ 0.,  0.,  0.],\n",
      "           [ 0.,  0.,  0.]]\n",
      "    \n",
      "      ones_like(x) = [[ 1.,  1.,  1.],\n",
      "                      [ 1.,  1.,  1.]]\n",
      "    \n",
      "    \n",
      "    \n",
      "    Parameters\n",
      "    ----------\n",
      "    data : NDArray\n",
      "        The input\n",
      "    \n",
      "    out : NDArray, optional\n",
      "        The output NDArray to hold the result.\n",
      "    \n",
      "    Returns\n",
      "    -------\n",
      "    out : NDArray or list of NDArrays\n",
      "        The output of this function.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(nd.ones_like)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "[[1. 1. 1.]\n",
       " [1. 1. 1.]]\n",
       "<NDArray 2x3 @cpu(0)>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = nd.array([[0,0,0],[2,2,2]])\n",
    "y = x.ones_like()\n",
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "nd.random.uniform?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "nd.random.uniform??"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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